Think Economics, Not Features, When Evaluating Big Data Value
Traditional enterprise data warehouse solutions helped to open the eyes of many organizations to the value of their data. Although these are significant systems, organizations quickly learned to monetize the actionable insight extracted from these systems, which led the rampant growth of the industry. Big data did not get big just from data growth. It got big because of its potential value, opportunities, and savings.
The more cost-efficiently you can capture a lot of data, plus the number of ways you can analyze it, equals the more worthwhile all that data could become. Value is results divided by costs. These (pseudo-)equations of big data value now extend not only to the disruptive power of transformative technologies like Hadoop, but also to increasingly popular cloud services for databases and data warehouses.
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